dz_13.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies = pd.read_csv('./netology-recsys-master/lecture-1/movies.csv')\n",
    "tags = pd.read_csv('./netology-recsys-master/lecture-1/tags.csv')\n",
    "ratings = pd.read_csv('./netology-recsys-master/lecture-1/ratings.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "tags_grpd = tags.groupby('movieId')['tag'].apply(lambda x: ' '.join(x))\n",
    "tags_unique = pd.DataFrame(tags['movieId'].unique(), columns=['movieId'])\n",
    "tags_grpd_df = pd.merge(tags_unique, tags_grpd, on='movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf = TfidfVectorizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf_tags = tf.fit_transform(tags_grpd_df['tag']).todense()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = [(k, tf.vocabulary_[k]) for k in tf.vocabulary_]\n",
    "cols = sorted(cols, key=lambda c: c[1])\n",
    "cols = [c[0] for c in cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "tags_features = pd.DataFrame(tf_tags, columns=cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_tags = pd.concat((tags_grpd_df, tags_features), axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## genres"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['gnr_splt'] = movies.genres.str.split('|')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['gnr_space'] = movies.apply(lambda r: ' '.join(r.gnr_splt), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf = TfidfVectorizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf_genres = tf.fit_transform(movies['gnr_space']).todense()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = [(k, tf.vocabulary_[k]) for k in tf.vocabulary_]\n",
    "cols = sorted(cols, key=lambda c: c[1])\n",
    "cols = [c[0] for c in cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "gnr_features = pd.DataFrame(tf_genres, columns=cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_genres = pd.concat((movies, gnr_features), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "del movies_genres['genres']\n",
    "del movies_genres['gnr_splt']\n",
    "del movies_genres['gnr_space']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "del movies_tags['tag']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "mgt = movies_genres.join(movies_tags, on='movieId', lsuffix='_genres', rsuffix='_tags')\n",
    "mgt = mgt.fillna(0)\n",
    "mgt.rename(columns={'movieId_genres':'movieId'}, inplace=True)\n",
    "\n",
    "del mgt['movieId_tags']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ## ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964981247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964983815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964982931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating  timestamp\n",
       "0       1        1     4.0  964982703\n",
       "1       1        3     4.0  964981247\n",
       "2       1        6     4.0  964982224\n",
       "3       1       47     5.0  964983815\n",
       "4       1       50     5.0  964982931"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_total = ratings.groupby('movieId')['userId'].count().reset_index(name = 'userId')\n",
    "ratings_total.columns = ['movieId', 'users']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_mean = ratings.groupby('movieId')['rating'].mean().reset_index(name = 'rating')\n",
    "ratings_mean.columns = ['movieId', 'rating_mean']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_users_count = len(ratings['userId'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_weighted = pd.merge(ratings_total, ratings_mean, on = 'movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings_weighted['rating_wgh'] = ratings_weighted['rating_mean'] * ratings_weighted['users'] / ratings_users_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "del ratings_weighted['users']\n",
    "del ratings_weighted['rating_mean']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "mgtr = mgt.join(ratings_weighted, on = 'movieId', lsuffix = '_mgt', rsuffix = '_rw')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "del mgtr['movieId_rw']\n",
    "\n",
    "mgtr.rename(columns={'movieId_mgt':'movieId'}, inplace=True)\n",
    "mgtr = mgtr.fillna(np.min(mgtr['rating_wgh']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## modeling time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>action_genres</th>\n",
       "      <th>adventure_genres</th>\n",
       "      <th>animation_genres</th>\n",
       "      <th>children_genres</th>\n",
       "      <th>comedy_genres</th>\n",
       "      <th>crime_genres</th>\n",
       "      <th>documentary_genres</th>\n",
       "      <th>drama_genres</th>\n",
       "      <th>...</th>\n",
       "      <th>you</th>\n",
       "      <th>younger</th>\n",
       "      <th>your</th>\n",
       "      <th>zellweger</th>\n",
       "      <th>zither</th>\n",
       "      <th>zoe</th>\n",
       "      <th>zombie</th>\n",
       "      <th>zombies</th>\n",
       "      <th>zooey</th>\n",
       "      <th>rating_wgh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.416846</td>\n",
       "      <td>0.516225</td>\n",
       "      <td>0.504845</td>\n",
       "      <td>0.267586</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.618852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.512361</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.620525</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.277869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.570915</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.027049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.505015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.466405</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.246721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.659836</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1769 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   movieId                               title  action_genres  \\\n",
       "0        1                    Toy Story (1995)            0.0   \n",
       "1        2                      Jumanji (1995)            0.0   \n",
       "2        3             Grumpier Old Men (1995)            0.0   \n",
       "3        4            Waiting to Exhale (1995)            0.0   \n",
       "4        5  Father of the Bride Part II (1995)            0.0   \n",
       "\n",
       "   adventure_genres  animation_genres  children_genres  comedy_genres  \\\n",
       "0          0.416846          0.516225         0.504845       0.267586   \n",
       "1          0.512361          0.000000         0.620525       0.000000   \n",
       "2          0.000000          0.000000         0.000000       0.570915   \n",
       "3          0.000000          0.000000         0.000000       0.505015   \n",
       "4          0.000000          0.000000         0.000000       1.000000   \n",
       "\n",
       "   crime_genres  documentary_genres  drama_genres  ...  you  younger  your  \\\n",
       "0           0.0                 0.0      0.000000  ...  0.0      0.0   0.0   \n",
       "1           0.0                 0.0      0.000000  ...  0.0      0.0   0.0   \n",
       "2           0.0                 0.0      0.000000  ...  0.0      0.0   0.0   \n",
       "3           0.0                 0.0      0.466405  ...  0.0      0.0   0.0   \n",
       "4           0.0                 0.0      0.000000  ...  0.0      0.0   0.0   \n",
       "\n",
       "   zellweger  zither  zoe  zombie  zombies  zooey  rating_wgh  \n",
       "0        0.0     0.0  0.0     0.0      0.0    0.0    0.618852  \n",
       "1        0.0     0.0  0.0     0.0      0.0    0.0    0.277869  \n",
       "2        0.0     0.0  0.0     0.0      0.0    0.0    0.027049  \n",
       "3        0.0     0.0  0.0     0.0      0.0    0.0    0.246721  \n",
       "4        0.0     0.0  0.0     0.0      0.0    0.0    0.659836  \n",
       "\n",
       "[5 rows x 1769 columns]"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mgtr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982703</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964981247</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982224</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>964983815</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964982931</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating  timestamp\n",
       "0       1        1     4.0  964982703\n",
       "1       1        3     4.0  964981247\n",
       "2       1        6     4.0  964982224\n",
       "3       1       47     5.0  964983815\n",
       "4       1       50     5.0  964982931"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100836, 4)\n",
      "(9742, 1769)\n"
     ]
    }
   ],
   "source": [
    "print(ratings.shape)\n",
    "print(mgtr.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_tfidf = pd.merge(ratings[['userId', 'movieId']], mgtr, on='movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
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       "3      15        1  Toy Story (1995)            0.0          0.416846   \n",
       "4      17        1  Toy Story (1995)            0.0          0.416846   \n",
       "\n",
       "   animation_genres  children_genres  comedy_genres  crime_genres  \\\n",
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       "\n",
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       "4                 0.0  ...  0.0      0.0   0.0        0.0     0.0  0.0   \n",
       "\n",
       "   zombie  zombies  zooey  rating_wgh  \n",
       "0     0.0      0.0    0.0    0.618852  \n",
       "1     0.0      0.0    0.0    0.618852  \n",
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       "4     0.0      0.0    0.0    0.618852  \n",
       "\n",
       "[5 rows x 1770 columns]"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_tfidf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.109016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45431</td>\n",
       "      <td>228</td>\n",
       "      <td>858</td>\n",
       "      <td>Godfather, The (1972)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.863943</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46218</td>\n",
       "      <td>228</td>\n",
       "      <td>3510</td>\n",
       "      <td>Frequency (2000)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46319</td>\n",
       "      <td>228</td>\n",
       "      <td>3555</td>\n",
       "      <td>U-571 (2000)</td>\n",
       "      <td>0.472152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.048361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47231</td>\n",
       "      <td>228</td>\n",
       "      <td>60069</td>\n",
       "      <td>WALL·E (2008)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.372684</td>\n",
       "      <td>0.461536</td>\n",
       "      <td>0.451361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48582</td>\n",
       "      <td>228</td>\n",
       "      <td>541</td>\n",
       "      <td>Blade Runner (1982)</td>\n",
       "      <td>0.446563</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>58053</td>\n",
       "      <td>228</td>\n",
       "      <td>610</td>\n",
       "      <td>Heavy Metal (1981)</td>\n",
       "      <td>0.336225</td>\n",
       "      <td>0.382705</td>\n",
       "      <td>0.473945</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>59149</td>\n",
       "      <td>228</td>\n",
       "      <td>1373</td>\n",
       "      <td>Star Trek V: The Final Frontier (1989)</td>\n",
       "      <td>0.497461</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.128689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>62527</td>\n",
       "      <td>228</td>\n",
       "      <td>2722</td>\n",
       "      <td>Deep Blue Sea (1999)</td>\n",
       "      <td>0.391122</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>62930</td>\n",
       "      <td>228</td>\n",
       "      <td>3005</td>\n",
       "      <td>Bone Collector, The (1999)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.320492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>63177</td>\n",
       "      <td>228</td>\n",
       "      <td>3113</td>\n",
       "      <td>End of Days (1999)</td>\n",
       "      <td>0.370356</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75095</td>\n",
       "      <td>228</td>\n",
       "      <td>1801</td>\n",
       "      <td>Man in the Iron Mask, The (1998)</td>\n",
       "      <td>0.602917</td>\n",
       "      <td>0.686265</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.082787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>77443</td>\n",
       "      <td>228</td>\n",
       "      <td>836</td>\n",
       "      <td>Chain Reaction (1996)</td>\n",
       "      <td>0.553065</td>\n",
       "      <td>0.629522</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>86098</td>\n",
       "      <td>228</td>\n",
       "      <td>1091</td>\n",
       "      <td>Weekend at Bernie's (1989)</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>91643</td>\n",
       "      <td>228</td>\n",
       "      <td>2986</td>\n",
       "      <td>RoboCop 2 (1990)</td>\n",
       "      <td>0.396688</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.459238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.064754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>91955</td>\n",
       "      <td>228</td>\n",
       "      <td>2013</td>\n",
       "      <td>Poseidon Adventure, The (1972)</td>\n",
       "      <td>0.602917</td>\n",
       "      <td>0.686265</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.634426</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 1770 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       userId  movieId                                              title  \\\n",
       "645       228       50                         Usual Suspects, The (1995)   \n",
       "1664      228      260          Star Wars: Episode IV - A New Hope (1977)   \n",
       "2769      228      362                            Jungle Book, The (1994)   \n",
       "6860      228     1196  Star Wars: Episode V - The Empire Strikes Back...   \n",
       "7932      228     1214                                       Alien (1979)   \n",
       "12745     228     2571                                 Matrix, The (1999)   \n",
       "16412     228      318                   Shawshank Redemption, The (1994)   \n",
       "28174     228       65                                    Bio-Dome (1996)   \n",
       "43716     228     1385                                 Under Siege (1992)   \n",
       "44582     228     1590                               Event Horizon (1997)   \n",
       "45431     228      858                              Godfather, The (1972)   \n",
       "46218     228     3510                                   Frequency (2000)   \n",
       "46319     228     3555                                       U-571 (2000)   \n",
       "47231     228    60069                                      WALL·E (2008)   \n",
       "48582     228      541                                Blade Runner (1982)   \n",
       "58053     228      610                                 Heavy Metal (1981)   \n",
       "59149     228     1373             Star Trek V: The Final Frontier (1989)   \n",
       "62527     228     2722                               Deep Blue Sea (1999)   \n",
       "62930     228     3005                         Bone Collector, The (1999)   \n",
       "63177     228     3113                                 End of Days (1999)   \n",
       "75095     228     1801                   Man in the Iron Mask, The (1998)   \n",
       "77443     228      836                              Chain Reaction (1996)   \n",
       "86098     228     1091                         Weekend at Bernie's (1989)   \n",
       "91643     228     2986                                   RoboCop 2 (1990)   \n",
       "91955     228     2013                     Poseidon Adventure, The (1972)   \n",
       "\n",
       "       action_genres  adventure_genres  animation_genres  children_genres  \\\n",
       "645         0.000000          0.000000          0.000000         0.000000   \n",
       "1664        0.432883          0.492725          0.000000         0.000000   \n",
       "2769        0.000000          0.548907          0.000000         0.664786   \n",
       "6860        0.432883          0.492725          0.000000         0.000000   \n",
       "7932        0.000000          0.000000          0.000000         0.000000   \n",
       "12745       0.446563          0.000000          0.000000         0.000000   \n",
       "16412       0.000000          0.000000          0.000000         0.000000   \n",
       "28174       0.000000          0.000000          0.000000         0.000000   \n",
       "43716       0.641630          0.000000          0.000000         0.000000   \n",
       "44582       0.000000          0.000000          0.000000         0.000000   \n",
       "45431       0.000000          0.000000          0.000000         0.000000   \n",
       "46218       0.000000          0.000000          0.000000         0.000000   \n",
       "46319       0.472152          0.000000          0.000000         0.000000   \n",
       "47231       0.000000          0.372684          0.461536         0.451361   \n",
       "48582       0.446563          0.000000          0.000000         0.000000   \n",
       "58053       0.336225          0.382705          0.473945         0.000000   \n",
       "59149       0.497461          0.000000          0.000000         0.000000   \n",
       "62527       0.391122          0.000000          0.000000         0.000000   \n",
       "62930       0.000000          0.000000          0.000000         0.000000   \n",
       "63177       0.370356          0.000000          0.000000         0.000000   \n",
       "75095       0.602917          0.686265          0.000000         0.000000   \n",
       "77443       0.553065          0.629522          0.000000         0.000000   \n",
       "86098       0.000000          0.000000          0.000000         0.000000   \n",
       "91643       0.396688          0.000000          0.000000         0.000000   \n",
       "91955       0.602917          0.686265          0.000000         0.000000   \n",
       "\n",
       "       comedy_genres  crime_genres  documentary_genres  ...  you  younger  \\\n",
       "645              0.0      0.553854                 0.0  ...  0.0      0.0   \n",
       "1664             0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "2769             0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "6860             0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "7932             0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "12745            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "16412            0.0      0.863943                 0.0  ...  0.0      0.0   \n",
       "28174            1.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "43716            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "44582            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "45431            0.0      0.863943                 0.0  ...  0.0      0.0   \n",
       "46218            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "46319            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "47231            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "48582            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "58053            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "59149            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "62527            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "62930            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "63177            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "75095            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "77443            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "86098            1.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "91643            0.0      0.459238                 0.0  ...  0.0      0.0   \n",
       "91955            0.0      0.000000                 0.0  ...  0.0      0.0   \n",
       "\n",
       "       your  zellweger  zither  zoe  zombie  zombies  zooey  rating_wgh  \n",
       "645     0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.006557  \n",
       "1664    0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.467213  \n",
       "2769    0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.009836  \n",
       "6860    0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.040164  \n",
       "7932    0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.118852  \n",
       "12745   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.001639  \n",
       "16412   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.035246  \n",
       "28174   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.073770  \n",
       "43716   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.006557  \n",
       "44582   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.109016  \n",
       "45431   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.023770  \n",
       "46218   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.023770  \n",
       "46319   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.048361  \n",
       "47231   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.000820  \n",
       "48582   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.004918  \n",
       "58053   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.022951  \n",
       "59149   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.128689  \n",
       "62527   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.004918  \n",
       "62930   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.320492  \n",
       "63177   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.013115  \n",
       "75095   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.082787  \n",
       "77443   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.022131  \n",
       "86098   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.010656  \n",
       "91643   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.064754  \n",
       "91955   0.0        0.0     0.0  0.0     0.0      0.0    0.0    0.634426  \n",
       "\n",
       "[25 rows x 1770 columns]"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user = user_tfidf[user_tfidf.userId==228]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "nn_cols = user_tfidf.columns[3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import NearestNeighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "nn = NearestNeighbors(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NearestNeighbors(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                 metric_params=None, n_jobs=None, n_neighbors=10, p=2,\n",
       "                 radius=1.0)"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.fit(user_tfidf[nn_cols])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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